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Relative-Position Estimation Based on Loosely Coupled UWB–IMU Fusion for Wearable IoT Devices

Computers, Materials & Continua 2023年第4期75卷 1941-1961页

作者： A.S.M.Sharifuzzaman Sagar Taein Kim Soyoung Park Hee Seh Lee Hyung Seok Kim Sejong University Seoul05006Korea Samsung Advanced Institute of Technology Suwon16678Korea

Relative positioning is one of the important techniques in collaborativerobotics, autonomous vehicles, and virtual/augmented reality (VR/AR)applications. Recently, ultra-wideband (UWB) has been utilized to calculaterelative position as it does not require a line of sight compared to a camerato calculate the range between two objects with centimeter-level ***, the single UWB range measurement cannot provide the relativeposition and attitude of any device in three dimensions (3D) because oflacking bearing information. In this paper, we have proposed a UWB-IMUfusion-based relative position system to provide accurate relative positionand attitude between wearable Internet of Things (IoT) devices in 3D. Weintroduce a distributed Euler angle antenna orientationwhich can be equippedwith the mobile structure to enable relative positioning. Moving average andmin-max removing preprocessing filters are introduced to reduce the standarddeviation. The standard multilateration method is modified to calculate therelative position between mobile structures. We combine UWB and IMUmeasurements in a probabilistic framework that enables users to calculatethe relative position between two nodes with less error. We have carried outdifferent experiments to illustrate the advantages of fusing IMU and UWBranges for relative positioning systems. We have achieved a mean accuracy of0.31m for 3D relative positioning in indoor line of sight conditions.

关键词： Relative position UWB IMU trilateration IoT bayesian filter

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Hybrid ToA and IMU indoor localization system by various algorithms

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Journal of Central South University 2019年第8期26卷 2281-2294页

作者： CHEN Xue-chen CHU Sheng LI Fan CHU Guang School of Electronics and Information Technology Sun Yat-Sen University Guangzhou 510275 China School of Metallurgy and Environment Central South University Changsha 410083 China

In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.

关键词： indoor localization time of arrival (ToA) inertial measurement unit (IMU) bayesian filter extended Kalman filter MAP algorithm

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Direct Target Tracking Using Laplace Approximation

Direct Target Tracking Using Laplace Approximation

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第三十九届中国控制会议

作者： Ji-An Luo Meng-Chun Guo Xue-Jun Liu Ke-Kang Song Yu-Xiang Yang Key Lab for IOT and Information Fusion Technology of Zhejiang Hangzhou Dianzi University

The direct tracking of a moving radio transmitter using spatially distributed receivers is considered based on delay and Doppler-shift induced signal waveforms. One key step for direct tracking is to approximate the generalized likelihood function corresponding to the largest eigenvalue of a Hermitian matrix. Although stochastic approximations can be set arbitrarily close to the optimal solution, these methods generally have high computational cost and tend to be inefficient when applied to high dimensional problems. In this paper, we develop a Laplace approximation approach for direct tracking using Taylor series expansions. The proposed method belongs to the deterministic approximation domain and therefore it is computational *** simulations validate the performance of the proposed method.

关键词： Direct Tracking bayesian filter Laplace Approximation

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